Liquid biopsies, based on cell free DNA (cfDNA) and proteins, have shown the potential to detect early stage cancers of diverse tissue types. However, most of these studies were retrospective, using individuals previously diagnosed with cancer as cases and healthy individuals as controls. Here, we developed a liquid biopsy assay, named the hepatocellular carcinoma screen (HCCscreen), to identify HCC from the surface antigen of hepatitis B virus (HBsAg) positive asymptomatic individuals in the community population. The training cohort consisted of individuals who had liver nodules and/or elevated serum α-fetoprotein (AFP) levels, and the assay robustly separated those with HCC from those who were non-HCC with a sensitivity of 85% and a specificity of 93%. We further applied this assay to 331 individuals with normal liver ultrasonography and serum AFP levels. A total of 24 positive cases were identified, and a clinical follow-up for 6–8 mo confirmed four had developed HCC. No HCC cases were diagnosed from the 307 test-negative individuals in the follow-up during the same timescale. Thus, the assay showed 100% sensitivity, 94% specificity, and 17% positive predictive value in the validation cohort. Notably, each of the four HCC cases was at the early stage (<3 cm) when diagnosed. Our study provides evidence that the use of combined detection of cfDNA alterations and protein markers is a feasible approach to identify early stage HCC from asymptomatic community populations with unknown HCC status.

Objective: Immune checkpoint inhibitors have revolutionized cancer therapy for multiple types of solid tumors, but as expected, a large percentage of patients do not show durable responses. Biomarkers that can predict clinical responses to immunotherapies at diagnosis are therefore urgently needed. Herein, we determined the associations between baseline gut commensal microbes and the clinical treatment efficiencies of patients with thoracic neoplasms during anti-programmed death protein 1 (PD-1) therapy. Methods: Forty-two patients with advanced thoracic carcinoma who received anti-PD-1 treatment were enrolled in the study. Baseline and time-serial stool samples were analyzed using 16S ribosomal RNA gene sequencing. Tumor responses, patient progression-free survival, and overall survival were used to measure clinical outcomes. Results: The diversities of the baseline gut microbiota were similar between responders (n = 23) and nonresponders (n = 19). The relative abundances of the Akkermansiaceae, Enterococcaceae, Enterobacteriaceae, Carnobacteriaceae and Clostridiales Family XI bacterial families were significantly higher in the responder group. These 5 bacterial families acted as a commensal consortium and better stratified patients according to clinical responses (P = 0.014). Patients with a higher abundance of commensal microbes had prolonged PFS (P = 0.00016). Using multivariable analysis, the abundance of the commensal consortium was identified as an independent predictor of anti-PD-1 immunotherapy in thoracic neoplasms (hazard ratio: 0.17; 95% confidence interval: 0.05-0.55; P = 0.003). Conclusions: Baseline gut microbiota may have a critical impact on anti-PD-1 treatment in thoracic neoplasms. The abundance of gut commensal microbes at diagnosis might be useful for the early prediction of anti-PD-1 immunotherapy responses.

Numerous metabolomics studies have been conducted to detect the metabolic mechanisms and biomarkers related to gastric cancer and colorectal cancer. Because of the common metabolic features between gastric cancer and colorectal cancer, a differential diagnosis is difficult. Here, we performed a systematic review and meta-analysis to identify differential metabolic biomarkers between these two types of cancers. Materials and Methods: PubMed, Embase, and ScienceDirect were searched to identify all metabolomics studies of gastric cancer and colorectal cancer published up to September 2018. Differential metabolites or altered pathways were extracted. The intersections and differences for these metabolites and pathways between gastric cancer and colorectal cancer were compared. Candidate biomarker sets for diagnosis were proposed from biofluid or feces by comparing them with tumor tissues. Results: Totally, 24 and 65 studies were included in gastric cancer and colorectal cancer, and 223 and 472 differential metabolites were extracted, respectively. Eight pathways were reproducibly enriched in blood, tissue and urine in gastric cancer, while, 11 pathways were reproducibly enriched in blood, urine, feces and tissue in colorectal cancer. Candidate metabolic biomarker sets in blood, urine, or feces for these two cancers were proposed. We found 27 pathways (categorized into eight classifications) common to both cancers, five pathways involving 35 metabolites enriched only in gastric cancer, and eight pathways involving 54 metabolites enriched only in colorectal cancer. Conclusion: The altered metabolic pathways showed signatures of abnormal metabolism in gastric cancer and colorectal cancer; the potential metabolic biomarkers proposed in this study have important implications for the prospective validation of gastric cancer and colorectal cancer.

Cetuximab improves the survival of patients with metastatic colorectal cancer. The main limitation is primary and secondary resistance, the underlying mechanism of which requires extensive investigation. We proved that PRSS expression levels are significantly negatively associated with the sensitivity of cancer cells to cetuximab. Detailed mechanistic analysis indicated that PRSS can cleave cetuximab, leading to resistance. Cetuximab or bevacizumab combined with SPINK1, a PRSS inhibitor, inhibited cell growth more efficiently than cetuximab or bevacizumab alone in xenograft models. PRSS levels in the serum of 156 patients with mCRC were analyzed, and poor efficacy of cetuximab therapy was observed in patients with aberrant PRSS expression. PRSS expression in monoclonal antibody (mAb)-treated patients with cancer from The Cancer Genome Atlas database was also evaluated to determine whether patients with higher PRSS expression have significantly reduced progression-free survival. Our work provides a strong scientific rationale for targeting PRSS in combination with cetuximab therapy.

No abstract

Background: Although massive studies have been conducted to investigate the mechanisms of esophageal squamous cell carcinoma (ESCC) carcinogenesis, the understanding of molecular alterations during the malignant transformation of epithelial dysplasia is still lacking, especially regarding epigenetic changes. Results: To better characterize the methylation changes during the malignant transformation of epithelial dysplasia, a whole-genome bisulfite sequencing analysis was performed on a series of tumor, dysplastic, and non-neoplastic epithelial tissue samples from esophageal squamous cell carcinoma (ESCC) patients. Promoter hypermethylation in TGF-β receptor type II (TGFBR2), an important mediator of TGF-β signaling, was identified. Further, we evaluated the methylation and expression of TGFBR2 in tumor samples through The Cancer Genome Atlas multiplatform data as well as immunohistochemistry. Moreover, treatment of ESCC cell lines with5-Aza-2′-deoxycytidine, a DNA methyltransferase inhibitor, reactivated the expression of TGFBR2. The lentiviral mediating the overexpression of TGFBR2 inhibited the proliferation of ESCC cell line by inducing cell cycle G2/M arrest. Furthermore, the overexpression of TGFBR2 inhibited the tumor growth obviously in vivo. Conclusions: The characterization of methylation silencing of TGFBR2 in ESCC will enable us to further explore whether this epigenetic change could be considered as a predictor of malignant transformation in esophageal epithelial dysplasia and whether use of a TGFBR2 agonist may lead to a new therapeutic strategy in patients with ESCC.

Background Low‐grade fetal adenocarcinoma of the lung (L‐FLAC) is a rare subtype of lung adenocarcinoma with undetermined histological features and genetic abnormalities. In this study, we attempted to investigate the pathological characteristics and genomic profiles of L‐FLAC. Methods Among 9839 cases of primary lung adenocarcinoma resected at Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College between January 2011 and June 2016, three cases diagnosed with L‐FLAC were selected. An immunohistochemical profile and whole exome sequencing (WES) using tumor and normal tissues was conducted. The last follow‐up date of patients was January 2021. Results Three cases diagnosed with L‐FLAC were finally screened, suggesting a percentage of 0.03%. All three patients were male and diagnosed as stage I following radical lobectomy. The missense variant was found to be the major gene mutation type using WES. CTNNB1 and DICER1 were the two most frequent gene mutations. All cases demonstrated positive TTF‐1 expression. In addition, two patients showed positive expression of β‐catenin (nuclear/cytoplasmic expression), CgA and Sny. Negative expression of PD‐L1 in tumor cells was observed in all three cases. One case with a relatively high tumor mutation burden (TMB) (2.18 mut/Mb) had an inferior overall survival of 11.5 months. However, the other two cases with a lower TMB (0.12 and 0.74 mut/Mb) still acquired disease‐free status up to the last follow‐up date. Conclusions L‐FLAC has a specific molecular background which is different from lung adenocarcinoma. Furthermore, gene heterogeneity was found and might be the reason for a dramatically different prognosis in these L‐FLAC patients.

Background: Colorectal cancer (CRC) is the result of complex interactions between the tumor's molecular profile and metabolites produced by its microenvironment. Despite recent studies identifying CRC molecular subtypes, a metabolite classification system is still lacking. We aimed to explore the distinct phenotypes and subtypes of CRC at the metabolite level. Methods: We conducted an untargeted metabolomics analysis of 51 paired tumor tissues and adjacent mucosa using ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry. Multivariate analysis including principal component analysis, orthogonal partial least squares discriminant analysis and heat maps, univariate analysis, and pathway analysis were used to identify potential metabolite phenotypes of CRC. Unsupervised consensus clustering was used to identify robust metabolite subtypes, and evaluated their clinical relevance. Results: A total of 173 metabolites (including nucleotides, carbohydrates, free fatty acids, and choline) were identified between CRC tumor tissue and adjacent mucosa. We found that lipid metabolism was closely related to the occurrence and progression of CRC. In particular, CRC tissues could be divided into three subtypes, and statistically significant correlations between different subtypes and clinical prognosis were observed. Conclusions: CRC tumor tissue exhibits distinct metabolite phenotypes. Metabolite differences between subtypes may provide a basis and direction for further clinical individualized treatment planning.